雪有多强?来自科罗拉多州Grand Mesa的NASA SnowEx SnowMicroPen数据的积雪承载能力和微观力学的空间相关性

IF 3.8 2区 工程技术 Q1 ENGINEERING, CIVIL Cold Regions Science and Technology Pub Date : 2025-03-01 Epub Date: 2024-11-26 DOI:10.1016/j.coldregions.2024.104369
Molly E. Tedesche, Aaron C. Meyer, Sergey N. Vecherin, Tate G. Meehan
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引用次数: 0

摘要

在微观和宏观尺度上,积雪的机械和结构特性对于理解积雪结构在每个冬天的演变至关重要。整个景观的积雪承载能力在空间上是非常可变的,但对于一系列应用来说,这是非常重要的。这些应用包括冬季车辆移动和模拟野生动物运动等。在这项研究中,我们使用来自NASA SnowEx 2017和2020野外活动的snomicropenetration meter (SMP)穿透力数据集,获得了科罗拉多州Grand Mesa地区积雪的微观结构和微观力学特性。首次对SnowEx活动的原始SMP数据进行处理和分析,利用涉及雪晶矩阵微观结构尺寸的经验和物理方法获得积雪微参数。我们提出了一个新的smp导出的雪承载能力微力学参数方程。我们还改进了一种在SMP原始数据中识别雪廓线上下边界的技术。本研究的最后一个组成部分涉及分析smp衍生的雪微参数在科罗拉多大梅萨的空间变异性。对这两个不同年份的统计分析结果揭示了空间关系的一致性。表现出非零交叉相关的微参数包括雪密度、抗压强度、承载能力和雪颗粒粘结破裂时的微观结构挠度。
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How strong is Snow? Spatial correlations of snowpack load bearing capacity and micromechanics from NASA SnowEx SnowMicroPen Data at Grand Mesa, Colorado
The mechanical and structural properties of a snowpack, at both the micro- and macro-scales, are critical to understanding how snow cover architecture evolves over each winter. Snow load bearing capacity across a landscape is extremely spatially variable, yet fundamentally important for an array of applications. Such applications include winter vehicle mobility and modeling wildlife movements, among others. In this study, we derive snowpack microstructural and micromechanical properties across Grand Mesa, Colorado using SnowMicroPenetrometer (SMP) penetration force datasets from the NASA SnowEx 2017 and 2020 field campaigns. For the first time, raw SMP data from the SnowEx campaigns are processed and analyzed to derive snow cover microparameters, using empirical and physical methods involving microstructural dimensions of the snow crystal matrix. We propose a newly created equation for an SMP-derived snow load bearing capacity micromechanical parameter. We also refine one technique for identifying top and bottom boundaries of snow profiles in SMP raw data.
The final component of this study involved an analysis of SMP-derived snow microparameter spatial variability across Grand Mesa, Colorado. Results of the statistical analyses for the two different years revealed consistency in spatial relationships. Microparameters that exhibited non-zero cross correlations included snow density, compression strength, load bearing capacity, and microstructural deflection during snow grain bond rupture.
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来源期刊
Cold Regions Science and Technology
Cold Regions Science and Technology 工程技术-地球科学综合
CiteScore
7.40
自引率
12.20%
发文量
209
审稿时长
4.9 months
期刊介绍: Cold Regions Science and Technology is an international journal dealing with the science and technical problems of cold environments in both the polar regions and more temperate locations. It includes fundamental aspects of cryospheric sciences which have applications for cold regions problems as well as engineering topics which relate to the cryosphere. Emphasis is given to applied science with broad coverage of the physical and mechanical aspects of ice (including glaciers and sea ice), snow and snow avalanches, ice-water systems, ice-bonded soils and permafrost. Relevant aspects of Earth science, materials science, offshore and river ice engineering are also of primary interest. These include icing of ships and structures as well as trafficability in cold environments. Technological advances for cold regions in research, development, and engineering practice are relevant to the journal. Theoretical papers must include a detailed discussion of the potential application of the theory to address cold regions problems. The journal serves a wide range of specialists, providing a medium for interdisciplinary communication and a convenient source of reference.
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